How digital health translational research is prioritised: a qualitative stakeholder-driven approach to decision support evaluation

ObjectivesDigital health is now routinely being applied in clinical care, and with a variety of clinician-facing systems available, healthcare organisations are increasingly required to make decisions about technology implementation and evaluation. However, few studies have examined how digital heal...

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Published inBMJ open Vol. 13; no. 11; p. e075009
Main Authors Bamgboje-Ayodele, Adeola, McPhail, Steven M, Brain, David, Taggart, Richard, Burger, Mitchell, Bruce, Lenert, Holtby, Caroline, Pradhan, Malcolm, Simpson, Mark, Shaw, Tim J, Baysari, Melissa T
Format Journal Article
LanguageEnglish
Published London British Medical Journal Publishing Group 06.11.2023
BMJ Publishing Group LTD
BMJ Publishing Group
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Abstract ObjectivesDigital health is now routinely being applied in clinical care, and with a variety of clinician-facing systems available, healthcare organisations are increasingly required to make decisions about technology implementation and evaluation. However, few studies have examined how digital health research is prioritised, particularly research focused on clinician-facing decision support systems. This study aimed to identify criteria for prioritising digital health research, examine how these differ from criteria for prioritising traditional health research and determine priority decision support use cases for a collaborative implementation research programme.MethodsDrawing on an interpretive listening model for priority setting and a stakeholder-driven approach, our prioritisation process involved stakeholder identification, eliciting decision support use case priorities from stakeholders, generating initial use case priorities and finalising preferred use cases based on consultations. In this qualitative study, online focus group session(s) were held with stakeholders, audiorecorded, transcribed and analysed thematically.ResultsFifteen participants attended the online priority setting sessions. Criteria for prioritising digital health research fell into three themes, namely: public health benefit, health system-level factors and research process and feasibility. We identified criteria unique to digital health research as the availability of suitable governance frameworks, candidate technology’s alignment with other technologies in use,and the possibility of data-driven insights from health technology data. The final selected use cases were remote monitoring of patients with pulmonary conditions, sepsis detection and automated breast screening.ConclusionThe criteria for determining digital health research priority areas are more nuanced than that of traditional health condition focused research and can neither be viewed solely through a clinical lens nor technological lens. As digital health research relies heavily on health technology implementation, digital health prioritisation criteria comprised enablers of successful technology implementation. Our prioritisation process could be applied to other settings and collaborative projects where research institutions partner with healthcare delivery organisations.
AbstractList OBJECTIVESDigital health is now routinely being applied in clinical care, and with a variety of clinician-facing systems available, healthcare organisations are increasingly required to make decisions about technology implementation and evaluation. However, few studies have examined how digital health research is prioritised, particularly research focused on clinician-facing decision support systems. This study aimed to identify criteria for prioritising digital health research, examine how these differ from criteria for prioritising traditional health research and determine priority decision support use cases for a collaborative implementation research programme.METHODSDrawing on an interpretive listening model for priority setting and a stakeholder-driven approach, our prioritisation process involved stakeholder identification, eliciting decision support use case priorities from stakeholders, generating initial use case priorities and finalising preferred use cases based on consultations. In this qualitative study, online focus group session(s) were held with stakeholders, audiorecorded, transcribed and analysed thematically.RESULTSFifteen participants attended the online priority setting sessions. Criteria for prioritising digital health research fell into three themes, namely: public health benefit, health system-level factors and research process and feasibility. We identified criteria unique to digital health research as the availability of suitable governance frameworks, candidate technology's alignment with other technologies in use,and the possibility of data-driven insights from health technology data. The final selected use cases were remote monitoring of patients with pulmonary conditions, sepsis detection and automated breast screening.CONCLUSIONThe criteria for determining digital health research priority areas are more nuanced than that of traditional health condition focused research and can neither be viewed solely through a clinical lens nor technological lens. As digital health research relies heavily on health technology implementation, digital health prioritisation criteria comprised enablers of successful technology implementation. Our prioritisation process could be applied to other settings and collaborative projects where research institutions partner with healthcare delivery organisations.
Objectives Digital health is now routinely being applied in clinical care, and with a variety of clinician-facing systems available, healthcare organisations are increasingly required to make decisions about technology implementation and evaluation. However, few studies have examined how digital health research is prioritised, particularly research focused on clinician-facing decision support systems. This study aimed to identify criteria for prioritising digital health research, examine how these differ from criteria for prioritising traditional health research and determine priority decision support use cases for a collaborative implementation research programme.Methods Drawing on an interpretive listening model for priority setting and a stakeholder-driven approach, our prioritisation process involved stakeholder identification, eliciting decision support use case priorities from stakeholders, generating initial use case priorities and finalising preferred use cases based on consultations. In this qualitative study, online focus group session(s) were held with stakeholders, audiorecorded, transcribed and analysed thematically.Results Fifteen participants attended the online priority setting sessions. Criteria for prioritising digital health research fell into three themes, namely: public health benefit, health system-level factors and research process and feasibility. We identified criteria unique to digital health research as the availability of suitable governance frameworks, candidate technology’s alignment with other technologies in use,and the possibility of data-driven insights from health technology data. The final selected use cases were remote monitoring of patients with pulmonary conditions, sepsis detection and automated breast screening.Conclusion The criteria for determining digital health research priority areas are more nuanced than that of traditional health condition focused research and can neither be viewed solely through a clinical lens nor technological lens. As digital health research relies heavily on health technology implementation, digital health prioritisation criteria comprised enablers of successful technology implementation. Our prioritisation process could be applied to other settings and collaborative projects where research institutions partner with healthcare delivery organisations.
Author McPhail, Steven M
Bruce, Lenert
Baysari, Melissa T
Pradhan, Malcolm
Bamgboje-Ayodele, Adeola
Taggart, Richard
Shaw, Tim J
Burger, Mitchell
Simpson, Mark
Holtby, Caroline
Brain, David
AuthorAffiliation 6 eHealth NSW , Chatswood , New South Wales , Australia
4 Murrumbidgee Local Health District , NSW Health , Wagga Wagga , New South Wales , Australia
5 Alcidion Pty Inc , Sydney , New South Wales , Australia
3 Sydney Local Health District , NSW Health , Camperdown , New South Wales , Australia
1 Biomedical Informatics and Digital Health, School of Medical Sciences, Faculty of Medicine and Health , The University of Sydney , Camperdown , New South Wales , Australia
2 Australian Centre for Health Service Innovation and Centre for Healthcare Transformation , Queensland University of Technology , Brisbane , Queensland , Australia
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SSID ssj0000459552
Score 2.3868828
Snippet ObjectivesDigital health is now routinely being applied in clinical care, and with a variety of clinician-facing systems available, healthcare organisations...
OBJECTIVESDigital health is now routinely being applied in clinical care, and with a variety of clinician-facing systems available, healthcare organisations...
Objectives Digital health is now routinely being applied in clinical care, and with a variety of clinician-facing systems available, healthcare organisations...
SourceID doaj
pubmedcentral
proquest
crossref
bmj
SourceType Open Website
Open Access Repository
Aggregation Database
Publisher
StartPage e075009
SubjectTerms Artificial intelligence
Collaboration
COVID-19
Data analysis
Health Informatics
Health services
Listening
Literature reviews
Medical research
Medical supplies
Pandemics
QUALITATIVE RESEARCH
Quality in health care
Stakeholders
Systematic review
Technology
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Title How digital health translational research is prioritised: a qualitative stakeholder-driven approach to decision support evaluation
URI https://bmjopen.bmj.com/content/13/11/e075009.full
https://www.proquest.com/docview/2889507620
https://search.proquest.com/docview/2886938092
https://pubmed.ncbi.nlm.nih.gov/PMC10632864
https://doaj.org/article/a9fc65e6b2ca49cc83f20a0740f0f0b9
Volume 13
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